CN108398666A - The polar system Parameters design of satellite-borne synthetic aperture radar - Google Patents
The polar system Parameters design of satellite-borne synthetic aperture radar Download PDFInfo
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Abstract
The invention belongs to electronic information technical field, the polar system Parameters design of specially a kind of satellite-borne synthetic aperture radar.The present invention is directed to Polarization target decomposition, Surface classification, military target detection and these four terminal applies of vegetation height inverting, it is proposed that the design method of polar system parameter.The polar system parameter includes one or more of polarization crosstalk, channel imbalance and system noise.Design method is all the correlation model established between terminal applies evaluation index and polar system parameter.Correlation model includes theoretical model formula or numerical value transitive relation.According to correlation model, and then it can propose the polar system parameter designing demand of corresponding terminal application.The present invention provides polar system Parameters design for spaceborne synthetic aperture radar (SAR) system designer, it can be ensured that the polarization sensitive synthetic aperture radar system of design can provide data service by application demand.
Description
Technical field
The invention belongs to electronic information technical field, the polar system parameter of specially a kind of satellite-borne synthetic aperture radar is set
Meter method.
Background technology
The image that polarimetric synthetic aperture radar system obtains can reflect the different scattering mechanism of atural object and polarization characteristic.Profit
It can carry out many applications, such as Polarization target decomposition, Surface classification with polarimetric synthetic aperture radar image, military target detects,
Vegetation height inverting etc..These applications will be helpful to people and understand ecoclimate environmental change, resource distribution, safeguard territorial security
Deng.
Although Polarization technique advantage is notable, the image that Changeable Polarization Radar System obtains is inevitably by system disturbance
The pollution of parameter.Polar system parameter refers mainly to polarization crosstalk, channel imbalance and system noise.In order to accurately using polarization
Information, polarization disturbance parameter must be corrected.Polarization data bearing calibration is paid close attention in existing research more, and is assumed after correcting
Data meet subsequent application demand [1] [2].Only a few studies pay close attention to specific polarization data application correction demand [3]
[4].And for system designer, understand that the System Parameter Design demand of terminal applies is very important.
For several typical cases of polarization data, i.e. Polarization target decomposition, Surface classification, military target detects and vegetation
It is extremely important that polar system parameter designing demand analysis is carried out in height inverting.These applications can help people to understand earth resource point
Cloth, Climate and Environment Variation and mankind's activity track.We must provide system polarization parameter design requirement, to ensure the conjunction of design
Data service can be provided at aperture radar system by application demand.In order to propose polar system parameter designing demand, we are intended to
Establish the correlation model and error transfer relationship between polar system parameter and the evaluation index of specific terminal applies.
For Polarization target decomposition and Surface classification application, many Polarization target decomposition parameters can be used for sensibility point
Analysis, such as angle of orientation, Cameron unit circles, the entropy parameter H that Cloude is decomposed, polarize rotation angle parameter α, removes orientation parameter u and v
[5][6][7][8].The parameter space being made of goal decomposition parameter can be used for class object and earth's surface.These goal decompositions
Method is equivalent equivalence under non-helical body hypothesis, and corresponding goal decomposition parameter can also mutually convert [9].
Military target probe algorithm has very much, their principle is to measure the similitude of two collision matrixes.It is common to calculate
Method has Yang methods [10] and Marino methods [11].The similitude that Yang methods pass through two target Mueller matrixes of measurement
To detect target.Marino methods detect target by measuring the coherence coefficient of two targets.
Forest is the important component of the ecosystem, detects the biomass of forest and helps to understand Climate and Environment Variation,
And the biomass of forest and Forest Vertical structure distribution are closely related.For inverting vegetation height, polarization information can be introduced
Interference handles to detach effective phase center of different scattering mechanisms, and this method is known as polarization interference technology [12] [13].Europe is empty
Office is planned to carry out BIOMASS tasks in the year two thousand twenty, and Global Forests biomass [14] is drawn by polarization interference measurement.In
State also plans to emit twin-L satellites to obtain forest height.
Polarization interference technology inverting vegetation height is that the EM scatter model based on vegetation carries out inverting, and one makes extensively
Forest EM scatter model is Random Volume over Ground (RVoG) [15] [16].The model builds vegetation
Mould is a double-layer structure, including random orientation particle layer and surface layer, and vegetation height, attenuation coefficient etc. can be used a small amount of
Vertical structure parameters describe.Finally according to RVoG models, the relationship of vegetation interference coherence and vegetation parameter can be established
[17][18]。
It, can inverting vegetation height from polarization interference measurement using known EM scatter model.Measured value is done again
The function that coherence is polarization base is related to, best height detection [19] can be obtained using relevant optimisation technique.It is relevant to optimize
Journey is exactly the linear combination that selection can make the maximum polarization base of coherence's amplitude.It can be obtained using relevant optimisation technique optimal
Volume scattering mechanism and ground scattering mechanism, to obtain best height detection.
The numerical value transitive relation between polar system parameter and the evaluation index of terminal applies is being established by numerical experiment
When, it needs artificially to add polar system error on the polarimetric synthetic aperture radar image of emulation.For polarity combination hole
The emulation of aperture radar image, mapping projections algorithm (Mapping and Projection Algorithm) can emulate a variety ofly
Table type, such as forest, farmland, city, road, river etc. [20].Two-way analytical ray-tracing algorithm (Bidirectional
Analytic Ray Tracing) a variety of man-made targets, such as aircraft, tank, naval vessel [21] can be emulated.PolSARproSim
Forest emulator can emulate the polarization interference data of vegetation, which is already integrated into European Space Agency PolSARpro education works
Have in case [22].
When carrying out statistical modeling to random vegetation height inversion error, need to use probability Distribution Model.Commonly
Statistical distribution pattern has rayleigh distributed, gamma distribution, K distributions, dead wind area etc. [23] [24] [25] [26].For from observation
Unknown model parameter is detected in data, the method that can be used has moments estimation, maximal possibility estimation, logarithm the Cumulant Method Using etc.
[27][28].In order to illustrate the reasonability of the model parameter of detection, qualitative assessment modeling accuracy is needed.Common interpretational criteria has
K-S distances, it is to assess modeling by comparing the deviation between observation data and the cumulative distribution function of statistical distribution pattern
[29] of precision.If deviation is zero, it is believed that statistical distribution functions have good modeling accuracy.
Invention content
It is an object of the invention to propose a kind of polar system Parameters design of satellite-borne synthetic aperture radar.This method
The polar system parameter designing demand of satellite-borne synthetic aperture radar can be provided for system designer, it is ensured that the synthetic aperture thunder of design
Data service can be provided up to system by application demand.
The present invention establishes the evaluation index and one of specific terminal applies from the angle of polarization sensitive synthetic aperture radar system designer
Kind or several polar system parameters and between correlation model, i.e. theoretical model formula or numerical value transitive relation, and then can obtain
The polar system parameter designing demand applied to corresponding terminal.Technical scheme of the present invention is specifically described as follows.
A kind of polar system Parameters design of satellite-borne synthetic aperture radar, for Polarization target decomposition, Surface classification,
Military target detection and these four terminal applies of vegetation height inverting are joined by establishing terminal applies evaluation index and polar system
Correlation model between number carries out polar system parameter designing, and correlation model includes that theoretical model formula or numerical value are transmitted and closed
System；The polar system parameter includes one or more of polarization crosstalk, channel imbalance and system noise；Wherein：For
Polarization target decomposition application, the correlation model formula for establishing evaluation index between the crosstalk that polarizes；For Surface classification application, build
Numerical relation between vertical evaluation index and the crosstalk that polarizes；For military target detection application, establishes evaluation index and polarization is gone here and there
Numerical relation between disturbing；For vegetation height inverting application, not only establish evaluation index and polarization crosstalk, channel imbalance and
Correlation model formula between system noise, the numerical value also obtained between evaluation index and these three polar system parameters transmit pass
System, theoretical model formula and numerical relation are mutually authenticated；Specific design method is as follows：
When terminal applies are Polarization target decomposition, evaluation index is orientation parameter p and scattering mechanism parameter g, using base
It is analyzed in the sensitivity theory of partial derivative, establishes polarization crosstalk δ1With orientation parameter disturbance quantity | Δ p |, scattering mechanism parameter perturbation
Amount | Δ g | between correlation model, the theoretical model formula is as follows：
Wherein:δ1For the crosstalk that polarizes, p1, k be intermediate variable.
And then obtain the polarization crosstalk demand of Polarization target decomposition application；
When terminal applies are Surface classification, evaluation index is polarization decomposing entropy parameter H, and polarize rotation angle parameter α, polarization
It removes to be orientated the parameter u for reflecting earth's surface dielectric characterization in theory, reflects the parameter v and Surface classification error of earth's surface scattering mechanism；
Four polarization decomposing parameter H, α, u and v and Surface classification error are to the crosstalk δ that polarizes2Sensibility use mapping projections algorithm MPA
The diameter radar image comprising a variety of ground surface types is emulated to carry out sensitivity analysis, establishes polarization crosstalk δ2With H,
Numerical value transitive relation between α, u, v and Surface classification error, and then obtain the polarization crosstalk demand of Surface classification application；
When terminal applies are that military target detects, evaluation index is target acquisition precision, and target acquisition precision is to polarization
Crosstalk δ3Sensibility emulation several scenes carried out using two-way analytical ray-tracing algorithm BART carry out sensitivity analysis, build
Vertical polarization crosstalk δ3Numerical value transitive relation between target acquisition precision, and then obtain the polarization string of military target detection application
Disturb demand；
When terminal applies are vegetation height inverting, evaluation index is vegetation height inversion error Δ, to by polar system
The perturbation matrix that parameter is constituted carries out Eigenvalues analysis, establishes be concerned with optimization vegetation height inversion error Δ and polarization crosstalk
δ4, channel amplitude it is uneven | f |, noise powerCorrelation model between three polar system parameters, the reason of the correlation model
It is as follows by formula：
Wherein：δ4For polarize crosstalk,For noise vector, A is constant, | f | it is uneven for channel amplitude,For noise work(
Rate；And then obtain the polarization crosstalk of vegetation height inverting application, channel amplitude imbalance and noise requirements；
In addition, when terminal applies are vegetation height inverting, the mean value of random vegetation height inversion error is to the crosstalk δ that polarizes4、
Channel amplitude is uneven | f | and noise powerSensibility using PolSARproSim forest emulators emulate scale Forest Scene come
Sensitivity analysis is carried out, the numerical value established between three polar system parameters and the mean value of vegetation height inversion error, which transmits, to close
System, and then obtain the polarization crosstalk of vegetation height inverting application, channel amplitude imbalance and noise requirements.The numerical relation and reason
It is mutually unified by relationship model formula.
In the present invention, when the terminal applies are Surface classification, the u-v-H parameter spaces of polarization parameter composition are to different
Ground surface type is classified；Earth's surface is divided into 9 classes on parameter space u-v-H, and the pixel classified by mistake of statistics is divided
Class error.
In the present invention, when the terminal applies are that military target detects, object detection method using Yang methods and
Marino methods.
In the present invention, when the terminal applies are vegetation height inverting, the scale Forest Scene of emulation is artificially added different
Polar system error, and then random vegetation height detection error is distributed with Gamma and is modeled, detect unknown model ginseng
Number μ can obtain the mean value of inversion error.
Compared to the prior art, the beneficial effects of the present invention are：The present invention from the angle of system designer, for
Several typical cases of polarization data have carried out polar system parameter designing demand analysis.These applications can help people to understand ground
Ball resource distribution, Climate and Environment Variation and mankind's activity track.The system polarization parameter design requirement that we provide, it can be ensured that
The polarization sensitive synthetic aperture radar system of design can provide data service by application demand.The present invention is the system of satellite-borne synthetic aperture radar
Designer provides polar system Parameters design.
Description of the drawings
Fig. 1 is scattering mechanism disturbance quantity in the embodiment of the present invention | Δ g | the map of magnitudes on Cameron unit circles.
Fig. 2 is orientation parameter disturbance quantity in the embodiment of the present invention | Δ p | and scattering mechanism disturbance quantity | Δ g | it is flat in g-p
Amplitude variation diagram on face.
Fig. 3 is the diameter radar image obtained based on MPA algorithm simulatings in the embodiment of the present invention.
Fig. 4 is distribution of the different earth's surface type areas in u-v-H planes in the embodiment of the present invention.
Fig. 5 is polarization decomposing parameter H, α, u and v in the embodiment of the present invention with polarization crosstalk δ2Change curve.
Fig. 6 is Surface classification error in the embodiment of the present invention with polarization crosstalk δ2Change curve.
Fig. 7 is that the UAV diameter radar images and Google Earth at the harbours San Diego in the embodiment of the present invention are taken photo by plane
Image.
Fig. 8 is polarization decomposing parameter H, α, u and the v at the harbours San Diego in the embodiment of the present invention with polarization crosstalk δ2
Change curve.
Fig. 9 is three kinds of typical military object modules in the embodiment of the present invention.
Figure 10 is the synthetic aperture radar of the different military targets obtained based on BART algorithm simulatings in the embodiment of the present invention
Image.
Figure 11 is the detecting error of Yang detectors in the embodiment of the present invention with polarization crosstalk δ3Change curve.
Figure 12 is the detecting error of Marino detectors in the embodiment of the present invention with polarization crosstalk δ3Change curve.
Figure 13 is that PolSARproSim scale Forest Scenes emulate schematic diagram and Pauli vector pseudo-colours in the embodiment of the present invention
Encode diameter radar image.
Figure 14 is forest height inversion result and forest height distribution histogram in the embodiment of the present invention.
Figure 15 be the embodiment of the present invention in Gamma fitting of distribution vegetation height inversion errors probability distribution histogram and
The result of cumulative distribution histogram.
Figure 16 is that Gamma distribution function modeling accuracies are assessed in the embodiment of the present invention.
Figure 17 is height detection error theory formula in the embodiment of the present invention and parameter μ with polarization crosstalk δ4Variation knot
Fruit compares.
Figure 18 be in the embodiment of the present invention height detection error theory formula and parameter μ with amplitude imbalance | f | change
Change Comparative result.
Specific implementation mode
It describes in detail with reference to the accompanying drawings and examples to technical scheme of the present invention.
The polar system Parameters design of satellite-borne synthetic aperture radar proposed by the present invention, from polarization sensitive synthetic aperture radar system
The angle of designer, establish specific terminal applies evaluation index and polar system parameter and between correlation model.The pass
Gang mould type includes theoretical model formula and numerical value transitive relation.The pole of corresponding terminal application can be proposed based on the correlation model
Change System Parameter Design demand.It elaborates to the present invention with reference to specific embodiment.
To Polarization target decomposition application, the present invention establishes polarization crosstalk δ1With the orientation parameter p of Polarization target decomposition and
Correlation model theoretical formula between scattering mechanism parameter g.Polarization decomposing parameter can be expressed as the function p (δ of polarization crosstalk1)
With g (δ1).By function p (δ1) and g (δ1) to δ1Ask first-order partial derivative that can obtain polarization decomposing parameter perturbation amount | Δ g | and | Δ
P | with polarization crosstalk δ1Between correlation model formula.The correlation model is suitable for deterministic coherent scattering target.The two
Polarization decomposing parameter has distinguished the different type of Polarization scattering target, and numerical value can be shown on Cameron unit circles.
In embodiment, we are according to the correlation model formula study being derived by disturbance quantity | Δ g | and | Δ p | mould
Formula figure.Scattering mechanism disturbance quantity | Δ g | the gradient map on Cameron unit circles is as shown in Figure 1.Fig. 1 shows that scattering mechanism is joined
The main offset of number g is from edge to center, and this contraction offset and angle of orientation p and scattering mechanism parameter g are proportional.
In addition to mainly deviating, it can also be observed that a kind of secondary offset is generated in region g → 1 when angle of orientation very little.In addition, disturbance
Amount | Δ g | and | Δ p | the offset in parameter g-p planes is as shown in Figure 2.At this point, the contraction offset of scattering mechanism parameter g is still
It can be clearly observable.The offset of orientation occurs mainly in lower right field, it can make the angle of orientation of the regional aim increase.Together
When, lower left corner region is not influenced by polarization crosstalk, that is, polarization characteristic is insensitive to crosstalk.
To Surface classification application, the present invention establishes polarization crosstalk δ2With polarization decomposing entropy parameter H, polarize rotation angle parameter
α, earth's surface dielectric parameter u, the numerical value transitive relation between earth's surface scattering mechanism parameter v and Surface classification error.In embodiment
In, we simulate the diameter radar image that L-band resolution ratio is 12m, simulating scenes packet using mapping projections algorithm MPA
Containing forest, farmland, city, road, a variety of ground surface types such as river, the image emulated is as shown in Figure 3.In figure 3, we
Select a variety of ground surface types for subsequent sensitivity analysis with red frame.The present embodiment calculates the polarization of selection region first
Resolution parameter, and classify to these earth's surfaces on parameter space u-v-H, classification results are as shown in Figure 4.As can be seen from Figure 4, this
A little regions are efficiently separated on u-v-H parameter spaces.
Different polarization crosstalks is added to the diameter radar image of emulation and polarization decomposing is carried out to selected areas, point
Four polarization decomposing parameter H, α, u and v are analysed to the crosstalk δ that polarizes2Sensibility.Wherein, polarization crosstalk δ2Change to from -42dB -
18dB.In the present embodiment, four polarization decomposing parameters are as shown in Figure 5 with the change curve of polarization crosstalk.It can from figure
Go out, when the crosstalk that polarizes is less than -32dB, the variation of four polarization decomposing parameters can be ignored.The variation of parameter u is than other three
Parameter is more sensitive, and when the crosstalk that polarizes is less than -25dB, the peak excursion of parameter u is less than 0.1, so it is considered that for nature
Surface classification, polarization crosstalk meet the requirement less than -25dB.
It, can be in parameter space u-v-H after the polarization decomposing parameter of typical earth surface area is calculated in the present embodiment
On earth's surface is divided into 9 classes.Under different polarization crosstalks, the pixel that mistake of statistics is classified on parameter plane u-v-H can obtain
To error in classification.Error in classification is with polarization crosstalk δ2Change curve it is as shown in Figure 6.As seen from the figure, when polarization crosstalk be less than-
When 25dB, error in classification is less than 10%.And when the crosstalk that polarizes increases to -18dB from -25dB, error in classification increases from 10% rapidly
Greatly to 44%.This result also demonstrates the -25dB polarization crosstalk demands that we propose natural terrain classification.By this implementation
Example obtain Surface classification application polarization crosstalk design requirement be：To make polarization decomposing parameter not change with polarization crossfire value
Become, and natural terrain error in classification is less than 10%, should ensure that polarization crosstalk is less than -25dB.
To Surface classification application, the present invention also in embodiment closes the UAV at the harbours San Diego obtained NASA/JPL
Pore-forming aperture radar image has carried out polarization crosstalk sensitivity analysis.UAV diameter radar images and corresponding Google take photo by plane
Image is as shown in Figure 7.Three pieces of regions are marked in figure and analyze for we, are city, sea and forest respectively.We assume that
The data are not by polarization crosstalk pollution, by emulating addition polarization crosstalk again.We analyze three pieces of areas in the present embodiment
Four polarization decomposing parameter H, α, u and v in domain are with polarization crosstalk δ2Change curve, the results are shown in Figure 8.From Fig. 8 we
Same conclusion can be obtained, i.e. natural terrain classification should meet the polarization crosstalk demand of at least -25dB.
To military target detection application, the present invention establishes polarization crosstalk δ3Numerical value between target acquisition error transmits
Relationship.In embodiment, we simulate several scenes to carry out sensibility point using two-way analytical ray-tracing algorithm BART
Analysis, the typical scene of emulation includes the aircraft on airport, the tank on meadow and the naval vessel on sea.It is imitated in the present embodiment
Genuine aircraft, tank, model ship are as shown in figures 9 a-9 c.We simulate 15 airplanes on airport, and 30 framves on meadow are smooth
Gram and sea on 30 naval vessels, these targets altogether have 0 °, 45 °, 90 °, 135 ° degree four kinds of azimuths.Emulate obtained synthesis
Aperture radar image has 1m resolution ratio, and simulation result is as shown in Figure 10 a-10c.
In the present embodiment, we carry out target acquisition using Yang methods and Marino methods, both pass through survey
The similitude of collision matrix is measured to detect target.Yang methods measure Mueller matrix similarities, and Marino methods, which measure, to be dissipated
Penetrate the coherence coefficient of vector.Simulating scenes are added with different polarization crosstalks, target is carried out respectively using two kinds of detection methods
Detection can obtain target acquisition error with polarization crosstalk δ3Change curve.The detecting error of Yang detectors is gone here and there with polarization
Disturb δ3Change curve as shown in figures 11a-11c, the detecting errors of Marino detectors is with polarization crosstalk δ3Change curve as scheme
Shown in 12a-12c.From change curve as can be seen that when the crosstalk that polarizes is more than -25dB, detecting error increases quickly.Pass through this
The polarization crosstalk design requirement for the military target detection application that embodiment obtains is：For the typical scene of emulation, to obtain extremely
Few 90% target acquisition precision should ensure that polarization crosstalk is less than -25dB.
To vegetation height inverting application, the present invention establishes vegetation height inversion error Δ and polarization crosstalk δ4, amplitude not
Balance | f | and noise powerBetween correlation model theoretical formula.We also establish vegetation height inversion error simultaneously
Mean value and three polar system parameters between numerical value transitive relation.In embodiment, we are gloomy using PolSARproSim
Woods emulator simulates a piece of 10m high broad-leaf forests on Bragg diffraction rough surface.The forest schematic diagram and Pauli of emulation
Vector pseudo-color coding diameter radar image is as shown in figure 13.Scene center border circular areas is forest, remaining is ground.It is gloomy
There is stronger back scattering in forest zone domain compared to ground.
In the present embodiment, the optimisation technique inverting vegetation height that is concerned with is used to the virgin forest scene that emulation obtains, instead
Result is drilled by the height true value as forest.Optimized coherence is solved to each pixel and detects height, the forest height of detection
Distribution map and forest height distribution histogram are as shown in figure 14.Wood land comes out in figure saliency, and height is almost the same.From
Find out in height distribution histogram, forest height is distributed in centered on 10m in smaller range.Count the mean value of forest height
For 10.06m, and emulation setting parameter very close to illustrating that inversion method effect is fine.
In the present embodiment, the scale Forest Scene obtained to emulation artificially adds different polar system errors, and to random
Vegetation height inversion error with Gamma be distributed modeled.With the crosstalk δ that polarizes4For=0.1, SNR=20dB, from getting dirty
Forest height is detected in the data of dye and counts the inversion error of each pixel.Using Gamma fittings of distribution inversion error and examine
Survey unknown model parameter.Figure 15 gives the Gamma results of fitting of distribution probability distribution histogram and cumulative distribution histogram.
Blue Streak represents the detection error observed in figure, and red matched curve is the Gamma distribution functions with particular model parameter.From
It can be seen that, Gamma distribution functions can be well matched with observation data, that is, vegetation inversion error can be given to provide very in Figure 15
Good modeling ability.
In the present embodiment, there are two model parameter μ and L, parameter μ to represent the mean value of distribution, parameter L for Gamma distributions tool
Influence the shape of Gamma distributions.Best matched curve can be obtained by adjustment parameter L, parameter μ reflects the spy of data
Sign, so we have counted the numerical value transitive relation between parameter μ and polar system parameter.To different signal-to-noise ratio and polarization crosstalk
Height detection error under combination carries out Gamma distributions and models and detect a group model parameter μ.Similarly, to different signal-to-noise ratio and
Height detection error under amplitude imbalance combination carries out Gamma distributions and models and detect a group model parameter μ.
In the present embodiment, it is reasonable in order to illustrate the model parameter of detection, we assess modeling using K-S distances
Precision.Modeling accuracy under different polar system parameter combinations is assessed with K-S distances, as a result as shown in figure 16.From figure
Find out, K-S distances are all very small, this illustrates that the Gamma distributed models that we use are good to the fitting effect for observing data, deviation
It is small.Good modeling accuracy illustrates that the model parameter μ that we detect under different polar system parameter combinations is correct.
In the present embodiment, we have obtained between model parameter μ and polarization crosstalk, channel amplitude imbalance and signal-to-noise ratio
Numerical value transitive relation.The numerical relation and the vegetation height inversion error Δ and three polar system parameters established in the present invention
Between correlation model theoretical formula be consistent, the two can be mutually authenticated.In fig. 17, we compared height detection mistake
Poor theoretical formula and parameter μ are with polarization crosstalk δ4Variation.In figure 18, we compared height detection error theory formula and
Parameter μ is with amplitude imbalance | f | variation.In both figures, discrete point represents the parameter μ value detected from observation data,
Dotted line represents the correlation model formula established in the present invention.It can be seen from the figure that dotted line and discrete point coincide substantially, and deviation
It is very small.This illustrate we establish vegetation height detection error and polar system parameter between correlation model theoretical formula and
Numerical value transitive relation is consistent.The polar system parameter designing demand of the vegetation height inverting application obtained through this embodiment
For：To make the average vegetation height inversion error caused by polar system error be less than 0.5m, signal-to-noise ratio should be better than 18dB,
The crosstalk that polarizes should be less than -25dB, and amplitude imbalance should be less than 0.5dB.
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Claims (4)
1. a kind of polar system Parameters design of satellite-borne synthetic aperture radar, which is characterized in that it is directed to Polarization target decomposition,
Surface classification, military target detection and vegetation height inverting these four terminal applies, by establish terminal applies evaluation index and
Correlation model between polar system parameter carries out polar system parameter designing, and correlation model includes theoretical model formula or number
It is worth transitive relation；The polar system parameter includes one or more of polarization crosstalk, channel imbalance and system noise；Its
In：For Polarization target decomposition application, the correlation model formula for establishing evaluation index between the crosstalk that polarizes；For Surface classification
Using the numerical relation for establishing evaluation index between the crosstalk that polarizes；For military target detection application, establish evaluation index and
Numerical relation between polarization crosstalk；For vegetation height inverting application, not only establishes evaluation index and polarize crosstalk, channel not
Correlation model formula between balance and system noise, also obtains the numerical value between evaluation index and these three polar system parameters
Transitive relation, theoretical model formula and numerical relation are mutually authenticated；Specific design method is as follows：
When terminal applies are Polarization target decomposition, evaluation index is orientation parameter p and scattering mechanism parameter g, using based on inclined
The sensitivity theory of derivative is analyzed, and polarization crosstalk δ is established1With orientation parameter disturbance quantity | Δ p |, scattering mechanism parameter perturbation amount |
Δ g | between correlation model, the theoretical model formula is as follows：
Wherein:δ1For the crosstalk that polarizes, p1, k be intermediate variable；
And then obtain the polarization crosstalk demand of Polarization target decomposition application；
When terminal applies are Surface classification, evaluation index is polarization decomposing entropy parameter H, and polarize rotation angle parameter α, and polarization goes to take
The parameter u for reflecting earth's surface dielectric characterization into theory, reflects the parameter v and Surface classification error of earth's surface scattering mechanism；Four
Polarization decomposing parameter H, α, u and v and Surface classification error are to the crosstalk δ that polarizes2Sensibility carried out using mapping projections algorithm MPA
The diameter radar image comprising a variety of ground surface types is emulated to carry out sensitivity analysis, establishes polarization crosstalk δ2With H, α, u,
Numerical value transitive relation between v and Surface classification error, and then obtain the polarization crosstalk demand of Surface classification application；
When terminal applies are that military target detects, evaluation index is target acquisition precision, and target acquisition precision is to the crosstalk δ that polarizes3
Sensibility emulation several scenes are carried out to carry out sensitivity analysis using two-way analytical ray-tracing algorithm BART, establish polarization
Crosstalk δ3Numerical value transitive relation between target acquisition precision, and then the polarization crosstalk for obtaining military target detection application needs
It asks；
When terminal applies are vegetation height inverting, evaluation index is vegetation height inversion error Δ, to by polar system parameter
The perturbation matrix of composition carries out Eigenvalues analysis, establishes be concerned with optimization vegetation height inversion error Δ and polarization crosstalk δ4, it is logical
Road amplitude imbalance | f |, noise powerCorrelation model between three polar system parameters, the theoretical formula of the correlation model
It is as follows：
Wherein：δ4For polarize crosstalk,For noise vector, A is constant, | f | it is uneven for channel amplitude,For noise power；Into
And obtain the polarization crosstalk of vegetation height inverting application, channel amplitude imbalance and noise requirements；
In addition, when terminal applies are vegetation height inverting, the mean value of random vegetation height inversion error is to the crosstalk δ that polarizes4, channel
Amplitude imbalance | f | and noise powerSensibility scale Forest Scene emulated using PolSARproSim forest emulators carry out
The numerical value transitive relation between three polar system parameters and the mean value of vegetation height inversion error is established in sensitivity analysis, into
And the polarization crosstalk of vegetation height inverting application, channel amplitude imbalance and noise requirements are obtained, the numerical relation and theoretical mould
Type relational expression is mutually unified.
2. polar system Parameters design according to claim 1, which is characterized in that the terminal applies are earth's surface point
When class, the u-v-H parameter spaces of polarization parameter composition classify to different ground surface types；Earth's surface is in parameter space u-v-H
On be divided into 9 classes, by mistake of statistics classify pixel obtain error in classification.
3. polar system Parameters design according to claim 1, which is characterized in that the terminal applies are military mesh
When mark detection, object detection method uses Yang methods and Marino methods.
4. polar system Parameters design according to claim 1, which is characterized in that the terminal applies are that vegetation is high
When spending inverting, random vegetation height inversion error is to carry out statistical modeling with Gamma distributions, and the mean value of inversion error passes through
Unknown model parameter μ is detected to obtain.
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